EBK STATISTICS FOR BUSINESS & ECONOMICS
12th Edition
ISBN: 9780100460461
Author: Anderson
Publisher: YUZU
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Chapter 16.4, Problem 18E
Jeff Sagarin has been providing sports ratings for USA today since 1985. In baseball his predicted RPG (runs/game) statistic takes into account the entire player’s offensive statistics, and is claimed to be the best measure of a player’s true offensive value. The following data show the RPG and a variety of offensive statistics for a recent Major League Baseball (MLB) season for 20 members of the New York Yankees. The labels on columns are defined as follows: RPG, predicted runs per game statistic; H, hits; 2B, doubles; 3B, triples; HR, home runs; RBI, runs batted in; BB, bases on balls (walks); SO, strikeouts; SB, stolen bases; CS, caught stealing; OBP, on-base percentage; SLG, slugging percentage; and AVG, batting average.
| Player | RPG | H | 2B | 3B | HR | RBI | BB | SO | SB | CS | OBP | SLG | AVG |
| D Jeter | 6.51 | 202 | 25 | 5 | 19 | 70 | 77 | 117 | 14 | 5 | .3S9 | .450 | .309 |
| H Matsui | 6.32 | 192 | 45 | 3 | 23 | 116 | 63 | 7S | 2 | 2 | .367 | .496 | .305 |
| A Rodriguez | 9.06 | 194 | 29 | 1 | 4S | 130 | 91 | 139 | 21 | 6 | .421 | .610 | .321 |
| G Sheffield | 6.93 | 170 | 27 | 0 | 34 | 123 | 7S | 76 | 10 | 2 | .379 | .512 | .291 |
| R Cano | 5.01 | 155 | 34 | 4 | 14 | 62 | 16 | 6S | 1 | 3 | .320 | .45S | .297 |
| B Williams | 4.14 | 121 | 19 | 1 | 12 | 64 | 53 | 75 | 1 | 2 | .321 | .367 | .249 |
| J Posada | 5.36 | 124 | 23 | 0 | 19 | 71 | 66 | 94 | 1 | 0 | .352 | .430 | .262 |
| J Giambi | 9.11 | 113 | 14 | 0 | 32 | S7 | 10S | 109 | 0 | 0 | .440 | .535 | .271 |
| T Womack | 2.91 | S2 | S | 1 | 0 | 15 | 12 | 49 | 27 | 5 | .276 | .2S0 | .249 |
| T Martinez | 5.0S | 73 | 9 | 0 | 17 | 49 | 3S | 54 | 2 | 0 | .32S | .439 | .241 |
| M Bellhorn | 4.07 | 63 | 20 | 0 | S | 30 | 52 | 112 | 3 | 0 | .324 | .357 | .210 |
| R Sierra | 3.27 | 39 | 12 | 0 | 4 | 29 | 9 | 41 | 0 | 0 | .265 | .371 | .229 |
| J Flaherty | 1.S3 | 21 | 5 | 0 | 2 | 11 | 6 | 26 | 0 | 0 | .206 | .252 | .165 |
| B Crosby | 3.4S | 27 | 0 | 1 | 1 | 6 | 4 | 14 | 4 | 1 | .304 | .327 | .276 |
| M Lawton | 5.15 | 6 | 0 | 0 | 2 | 4 | 7 | S | 1 | 0 | .263 | .250 | .125 |
| R Sanchez | 3.36 | 12 | 1 | 0 | 0 | 2 | 2 | 3 | 0 | 1 | .326 | .302 | .279 |
| A Phillips | 2.13 | 6 | 4 | 0 | 1 | 4 | 1 | 13 | 0 | 0 | .171 | .325 | .150 |
| M Cabrera | 1.19 | 4 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | .211 | .211 | .211 |
| R Johnson | 3.44 | 4 | 2 | 0 | 0 | 0 | 1 | 4 | 0 | 0 | .300 | .333 | .222 |
| F Escalona | 5.31 | 4 | 1 | 0 | 0 | 2 | 1 | 4 | 0 | 0 | .375 | .357 | .2S6 |
Let the dependent variable be the RPG statistic.
- a. Develop the best one-variable estimated regression equation.
- b. Use the methods in this section to develop the best estimated multiple regression equation for predicting a player’s RPG.
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Chapter 16 Solutions
EBK STATISTICS FOR BUSINESS & ECONOMICS
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